THE FIELD ORIENTED CONTROL OF A PERMANENT MAGNET

SYNCHROUNOUS MOTOR (PMSM) BY USING FUZZY LOGIC

SAMAT BIN IDERUS

A project report submitted in partial fulfillment of the

requirement for the award of the

Degree of Master of Electrical Engineering

Faculty of Electrical and Electronic Engineering

University Tun Hussein Onn Malaysia

JANUARY 2014

vi

ABSTRACT

This project presents the comprehensive performance analysis on the principle of

operation, design considerations and control algorithms of the field oriented control

(FOC) for a permanent magnet synchronous motor (PMSM) drive system of Fuzzy

Logic Controller (FLC) and proportional-integral PI for speed control in closed loop

operation. To perform speed control of typical PMSM drives, PI controllers and FOC

method are classically used. PI Controller controller suffers from the drawback that for

its proper performance, the limits of the controller gains and the rate at which they

would change have to be appropriately chosen. Fuzzy based gain scheduling of PI

controller has been proposed in which uses in order to overcome the PI speed

controller problem. The simulation results show that the proposed FLC speed

controller produce significant improvement control performance compare to the PI

controller. FLC speed controller produced a better performance than PI speed

controller where the overshoot is totally removed and the settling time faster than PI

speed controller in achieving desired output speed. The fuzzy algorithm is based on

human intuition and experience and can be regarded as a set of heuristic decision rules.

It is possible to obtain very good performance in the presence of varying load

conditions changes of mechanical parameters and inaccuracy in the process modelling.

Research and application of fuzzy logic are developing very rapidly, with promising

impacts on electric drives and power electronics in future.

Keywords: FOC, PMSM, FLC, PI and for Speed Control.

vii

ABSTRAK

Projek ini membentangkan analisis prestasi yang komprehensif tentang prinsip

operasi , pertimbangan reka bentuk dan algoritma field oriented control ( FOC) untuk

motor segerak magnet kekal ( MSMK ) sistem kawalan Logik Fuzzy dan pengawal

PI adalah penting untuk mengawal kelajuan beroperasi gelung tertutup. Untuk

melaksanakan kawalan kelajuan pemacu PMSM, kebiasaannya pengawal PI dan

kaedah FOC adalah klasik digunakan. Pengawal PI mengalami kelemahan dari segi

prestasi. Logik Fuzzy beroperasi berasaskan pengawal PI telah dicadangkan di mana

menggunakan untuk mengatasi masalah pengawal kelajuan PI. Keputusan simulasi

menunjukkan bahawa kelajuan pengawal FLC yang dicadangkan menghasilkan

prestasi kawalan peningkatan yang ketara berbanding dengan pengawal PI. Pengawal

kelajuan Logik Fuzzy menghasilkan prestasi kawalan kelajuan yang lebih baik

daripada PI kelajuan pengawal di mana terlajak sama sekali dikeluarkan dan masa

pengenapan lebih cepat daripada kelajuan pengawal PI dalam mencapai kelajuan

output yang dikehendaki. Pengawal logik adalah berdasarkan kepada gerak hati dan

pengalaman manusia dan boleh dianggap sebagai satu set peraturan keputusan

heuristik. Ia adalah mungkin untuk mendapatkan prestasi yang sangat baik di

hadapan pelbagai keadaan beban perubahan parameter mekanikal dan ketidaktepatan

dalam pemodelan proses. Penyelidikan dan aplikasi logik kabur membangun dengan

pesat, dengan kesan cerah pada pemacu elektrik dan elektronik kuasa pada masa

akan datang.

viii

CONTENTS

TITLE i

THESIS STATUS CONFIRMATION ii

DECLARATION iii

DEDICATION iv

ACKNOWLEDGEMENT v

ABSTRACT vi

ABSTRAK vii

TABLE OF CONTENT viii

LIST OF FIGURES x

LIST OF TABLES xii

LIST OF APPENDINDICIES xiii

LIST OF ABBREVIATIONS xiv

CHAPTER 1 INTRODUCTION

1.1 Overview 1

1.2 Background of study 1

1.3 Problem statement 3

1.4 Project’s objectives 3

1.5 Scopes 4

1.6 Dissertation outline 4

xi

CHAPTER 2 LITERATURE REVIEW

2.1 Overview 6

2.2 AC motor control schemes 6

2.3 Principle of vector control 8

2.4 Field oriented control 9

2.4.1 Space vector definition and projection 10

2.4.2 The Clarke transformation 11

2.4.3 The Park transformation 12

2.5 Space vector pulse width modulation 13

2.6 Permanent magnet synchronous motor 15

2.6.1 Advantages of PMSM 18

2.7 Fuzzy logic controller 19

2.8 Previous works 20

CHAPTER 3 METHODOLOGY

3.1 Overview 23

3.2 System architecture 24

3.3 Phase A 25

3.3.1 Dynamic modelling of PMSM 25

3.3.2 Field oriented control technique 27

3.4 Phase B 30

3.4.1 Development of fuzzy logic controller 30

3.4.2 Space vector PWM (SVPWM) module 33

3.5 Summary of works 35

CHAPTER 4 RESULT AND DATA ANALYSIS

4.1 Overview 36

4.2 System modeling 36

4.3 Case I: System simulation during no load condition 37

4.3.1 Speed response of PI and FLC controller

. during no load condition.

37

4.3.2 Comparison between PI and FLC controller 39

4.3.3 Current response for PI and FLC controller 41

xii

432.4 Electromagnetic torque Response 43

4.4 Case II: System simulation with FLC controller

. during no load condition

45

4.4.1 Speed response of PI and FLC controller

. during load condition

46

4.4.2 Comparison between PI and FLC controller 47

4.4.3 Current response for PI and FLC controller 49

4.4.4 Torque response for PI and FLC controller 51

4.5 Summary of works 52

CHAPTER 5 CONCLUSION, DISCUSSION AND

RECOMMENDATION

5.1 Overview 54

5.1 Discussion 54

5.2.1 Case I: System simulation during no load

. condition

55

5.2.1 Case II: System simulation during load

. condition

56

5.2 Conclusion 57

5.3 Recommendations and future works 57

REFERENCES 59

VITA 62

APPENDIX 63

x

LIST OF FIGURES

2.1 AC motor control schemes 7

2.2 Conventional vector control of PMSM 8

2.3 Stator current space vector and its component in (a,b,c) 10

2.4 Stator current space vector and its components in (a,b) 11

2.5 Stator current space vector and Its Component in (a,b) and in

The d,q rotating reference frame

12

2.6 Voltage space vector locations corresponding to different

switching states

14

2.7 Classification of electric motors 16

2.8 A three-phase synchronous motor with a one permanent

magnet pair pole rotor

17

2.9 Surface permanent magnet motor 17

2.10 The basic structure of fuzzy logic controller 19

3.1 Block diagram of proposed system 24

3.2 Transformation in FOC 28

3.3 PMSM model with FOC system controlled by PI 29

3.4 Block diagram of fuzzy logic controller 30

3.5 Membership functions of the input (error) linguistic variables 31

3.6 Membership functions of the input (de-error) linguistic

variables

31

3.7 Membership functions of the output linguistic variables 31

3.9 Demonstrated rules in 3D surface view 32

3.10 Phase voltage space vectors 34

xi

4.1 System modelling of PI speed controller in Simulink. 37

4.2 Start up speed response (rad/s) for PMSM by using PI

controller.

38

4.3 Start up speed response (rad/s) for PMSM by using FLC

controller.

39

4.4 Simulated speed responses by using FLC and PI controller 40

4.5 Phase currents response (rad/s) for PMSM by using PI

controller

41

4.6 Phase currents response (rad/s) for PMSM by using FLC

controller.

42

4.7 Torque response (rad/s) for PMSM by using PI controller. 43

4.8 Torque response (rad/s) for PMSM by using FLC controller 44

4.9 System modeling of PI speed controller in Simulink during

load condition

45

4.10 System modeling of FLC speed controller in Simulink

during load condition

45

4.11 Start up speed response (rad/s) for PMSM by using PI

controller with mechanical load connected.

46

4.12 Start up speed response (rad/s) for PMSM by using FLC

controller with mechanical load connected.

47

4.13 Start up speed response (rad/s) by using PI and FLC

controller with mechanical load connected.

48

4.14 Start up current response by using PI controller with

mechanical load connected.

49

4.15 Start up current response by using FLC controller with

mechanical load connected

50

4.16 Torque response (rad/s) for PMSM by using PI controller

during loading condition

51

4.17 Torque response (rad/s) for PMSM by using FLC controller

loading condition

52

xii

LIST OF TABLES

2.1 Phase to neutral space vector for three phase voltage source

inverter

14

2.2 Survey on previous works 20

3.1 The fuzzy logic rule 32

xiii

LIST OF APPENDICES

APPENDIX TITLE PAGE

A Structures approach for development of project activities 63

B Pmsm parameter 64

C Gannt chart for master’s project I 65

D Gannt chart for master’s projectII 66

xiv

LIST OF SYMBOLS AND ABBREVIATIONS

A - Ampere

AC - Alternating Current

DC - Direct Current

DTC - Direct Torque Control

FLC - Fuzzy Logic Controller

FOC - Field Oriented Control

Hz -Hertz

IPMSM - Interior Permanent Magnet Synchronous Motor

Nm - Newton meter

PI - Proportional Integral

PMSM - Permanent Magnet Synchronous Motor

rad/s - Radian per second

SM - Synchronous Motor

SVPWM - Space Vector Pulse Modulation

V - Volts

VC - Vector Control

CHAPTER 1

INTRODUCTION

1.1 Overview

In this chapter, the introduction of the project will be clarified in detail in which

consists of the project background towards the focusing of the project study, problem

statement, project objective, research scopes and project outline.

1.2 Background of study

In recent years, the permanent-magnet synchronous motor (PMSM) has emerged as an

alternative to induction motor due to the increasing energy saving demand. PMSM are

widely used in high-performance applications such as industrial robots and machine

tools because of its compact size, high-power density, high air-gap flux density, high-

torque/inertia ratio, high torque capability, high efficiency and free maintenance [1-

6,10-12,17-20].

2

The Advancements in magnetic materials, semiconductor power devices and

control theories have made the PMSM drives play a vitally important role in motion-

control applications. The rotor of PMSM is connected to the load that cause low

pulsation torque quality. Overlapping control during phase transition may also trim

down the torque pulsation [2-5]. For this PMSM required the power inverter to operate

at higher switching frequency. So that it attains overlap control and noise reduction but

result is high switching losses and lessening in the overall drive efficiency [6,7].

In order to achieve the desired performances of PMSMs as the behavior of DC

motors, direct control of stator currents is needed. Nevertheless, it is quite unattainable

due to the strong coupling and nonlinear natures of the AC motors. Hence, to realize

the decoupling of relevant variables, a particular algorithm must be introduced.

Fortunately, this problem has been resolved by the vector control technology, often

referred to as Field-Oriented-Control (FOC) [3,10,11-15,18&23].

The principle of FOC was first proposed by F. Blaschke of Siemens in the early

1970s for controlling induction motors. This method had been developed into a

complete theory system within several years of efforts [8,9]. FOC of PMSM motor

drive gives improved performance in terms of faster dynamic response and more

efficient operation. The FOC or vector control method gives the performance

characteristics similar to that of a dc machine which are considered desirable in certain

applications[10,11].Vector controlled PMSM drive provides better dynamic response

and lesser torque ripples, and necessitates only a constant switching frequency.

Proportional plus integral (PI) controllers are usually preferred, but due to its

fixed proportional gain and integral time constant, the performance of the PI controllers

are affected by parameter variations, load disturbances and speed variations [1,2&12].

The complexity of PI controller tuning and high response time is overcome by Fuzzy

controller [1,2,4&12].

3

1.3 Problem statement

Vector controlled PMSM drive provides better dynamic response and lesser torque

ripples, and necessitates only a constant switching frequency. With the advent of the

vector control methods, permanent magnet synchronous motor can be operated like

separately excited dc motor high performance application.

The complexity of conventional Proportional plus integral (PI) controller has

low speed control performance such as high overshoot and less response time can be

overcome by Fuzzy logic controller [1,2,4,12,19,20 & 22]. Which has less response

time and high accuracy without any mathematical calculation [1,2,4,12,19,20&22].This

project presents a simulation of speed control system on fuzzy logic approach for an

indirect vector controlled permanent magnet synchronous drive by applying space

vector modulation.

1.4 Objectives

The main objective of the project is to describe a comprehensive analysis on the

principle of operation, design considerations and control algorithms of a PMSM drives

speed control system, in order to improved speed control performance of PMSM such

as low overshoot, fast response time, low torque and current ripple.

The performances of the proposed FLC based system are investigated and

compared to those obtained from the conventional PI controller based drive using

commercially available software MATLAB/SIMULINK at different dynamic operating

conditions such as sudden change in command speed with no load and load condition.

4

1.5 Scopes of project

The area covered by an activity or topic are quit wide. The scopes of the project are

limited as follows:

(i). To model a Permanent Magnet Synchronous motor (PMSM) by using

mathematical modeling in MATLAB Simulink software.

(ii). To develop fuzzy logic controller based on field oriented control of vector

control in order to control PMSM speed. The fuzzy logic controller are executes

the rule based taking inputs and give output by defuzzification.

(iii). To test the performance of Fuzzy Logic controller comparing to PI controller by

using simulation. The design analysis of speed control of a PMSM realized in

MATLAB Simulink software.

1.6 Dissertation outlines

The project dissertation is basically to document the concept, implementation and

outcome of the project which relevant to the project progress. This dissertation is

organized into five main chapters which are introduction, literature reviews, and

methodology, result analysis and conclusion.

(i). Chapter 1 discussed the background and general idea of the proposed project.

Besides that, the objectives and scopes of the project are explained in detail in

this chapter.

(ii). Chapter 2 discovered the reviews of the literature which includes the principles

of Field Oriented control technique implemented in controlling PMSM drive.

5

Some basis Space Vector Pulse Width Modulation (SVPWM) theory and the

brief reviews of the fuzzy logic also mentioned in this chapter.

(iii). Chapter 3 shows the methodology/steps of each design stage. The details of the

topology are discussed in this chapter with the operations of the system.

(iv). Chapter 4 presents the various results are shown and discussed from the

simulation results and analysed the compensation performance of the proposed

Fuzzy Logic Controller (FLC) in comparing with traditional Proportional

Integral (PI) controller of speed control system on PMSM drive system. The

simulation results of the systems performance have been observed.

(v). Chapter 5 states the conclusions or outcome simulation results of the systems

performance have been observed of this project and the recommendation for the

further work in order to improve this project are discussed in this chapter.

6

CHAPTER 2

LITERATURE REVIEWS

2.1 Overview

In this chapter consist of the several definitions and theoretical background of AC

motor control, permanent magnet synchronous motor (PMSM) and fuzzy logic

approach. This chapter also discussed the previous works or regarding this project are

discussed which will be used to analyze the simulation and experimental data.

2.2 AC motor control schemes

High performance drives refers to the drive system ability to offer precise control to a

rapid dynamic response and a good steady state response. Several techniques involved

to control AC machines speed, flux and torque. The basic controlling parameters are

the voltage and the frequency of the applied voltages/currents, and thus are not suitable

for obtaining controlled operation of machines [13].

7

The power electronic converter has been introduced to control interface between

grid supply and the electric motors. In most cases AC-DC-AC converters are used for

AC machines drives and extremely complex. These AC-DC-AC converters most

commonly called as inverter and are used to feed the motors for adjustable speed

applications. Other alternatives are direct AC-AC converters, such as cyclo-converter

and matrix converter. However these converters experienced from some drawbacks,

including the limited output frequency for cyclo-converter and matrix converter will

experience 86% of input voltage magnitudes [13]. Figure 2.1 illustrated the AC motor

control schemes can be divided into two main controls.

AC Motor Control

Scalar Based

Vector Control

Field Oriented

Control

Non-Linear

ControlPredictive Control

Direct Torque

Control

Frequency/No

PolesV/f= Constant

Figure 2.1: AC motor control schemes [13].

Scalar controls are easy to implement and offer steady-state response, but the

dynamics are slow. Vector control with closed loop feed back control has introduced in

order to obtain high precision, good dynamics and steady-state response. Direct torque

control (DTC) is control schemes for low and medium speed applications. In However,

in high speed case, it becomes very hard to realize DTC. It is caused mainly by

necessity of high sampling rate, which is hard to obtain in high velocity range [13]. .

Drawbacks of scalar control and DTC, moves the scope on the field oriented control

(FOC) solution [13].

8

2.3 Principle of vector control

The invention of vector control (VC) in the beginning of 1970’s and demonstrated in

induction motor can be controlled by separately excited DC motor, which increase the

efficiency of AC drives [6]. In VC the instantaneous position of voltage, current, and

flux space vectors are controlled, ideally giving correct orientation both in steady state

and during transients. Vector control is applicable to both Asynchronous and

synchronous motor drive. The Figure.2.2 shows the block diagram of conventional

vector control of PMSM [6].

Figure 2.2: Conventional vector control of PMSM [6].

The synchronous inductance and the corresponding armature flux very small that

is, Ψs= Ψm= Ψf. The produced torque expression can be presented as equation 2.1

(2.1)

9

This indicates that the torque is proportional to power factor angle φ equals the

torque angle δ as presented in equation 2.2

(2.2)

The stator command current is derived from the speed control loop.

2.4 Field Oriented Control

The Field Orientated Control (FOC) consists of controlling the stator currents

represented by a vector [10,11,15]. This control is based on projections which

transform a three phase time and speed dependent system into a two co-ordinate (d and

q co-ordinates) time invariant system. These projections lead to a structure similar to

that of a DC machine control.

Field orientated controlled machines need two constants as input references: the

torque component (aligned with the q co-ordinate) and the flux component (aligned

with d co-ordinate). As FOC is simply based on projections the control structure

handles instantaneous electrical quantities. This makes the control accurate in every

working operation (steady state and transient) and independent of the limited

bandwidth mathematical model. The FOC thus solves the classic scheme problems, in

the following ways :

(i). The ease of reaching constant reference

(ii). The ease of applying direct torque control.

10

2.4.1 Space vector definition and projection

The three-phase voltages, currents and fluxes of AC-motors can be analyzed in terms of

complex space vectors [15]. With regard to the currents, the space vector can be

defined as follows. Assuming that , , and ,are the instantaneous currents in the

stator phases, then the complex stator current vector is defined by [11,15,16]:

(2.3)

where

and

are present the spatial operators. The following diagram

shows the stator current complex space vector:

Figure 2.3: Stator current space vector and its component in (a,b,c) [15]

where (a,b,c) are the three phase system axes. This current space vector depicts the

three phase sinusoidal system. It still needs to be transformed into a two time invariant

co-ordinate system. This transformation can be split into two steps:

(i). (a,b,c) → (α, β) (the Clarke transformation) which outputs a two co-ordinate

time variant system.

11

(ii). (α, β) → (d,q) (the Park transformation) which outputs a two co-ordinate time

invariant system

2.4.2 The Clarke transformation

The space vector can be reported in another reference frame with only two orthogonal

axis called (α, β). Assuming that the axis a and the axis α are in the same direction as

the following vector diagram [11,15]:

Figure 2.4: Stator current space vector and its components in (a,b) [15].

The projection that modifies the three phase system into the (a,b) two dimension

orthogonal system is presented below.

√

√ (2.4)

12

2.4.3 The Park transformation

This projection modifies a two phase orthogonal system (α, β) in the d,q rotating

reference frame. Consider the d axis aligned with the rotor flux, the next diagram

shows, for the current vector, the relationship from the two reference frame [11,15]:

Figure 2.5: Stator current space vector and its component in (a,b) and in the d,q rotating

reference frame [15].

Where θ is the rotor flux position. The flux and torque components of the current vector

are determined by the following equations:

(2.5)

These components depend on the current vector (a,b) components and on the rotor flux

position.

13

2.5 Space vector pulse width modulation

The space vector pulse width modulation (SVPWM) technique of the most popular

technique due to a higher DC bus voltage and offered easy digital realization [8,14,16].

the concept of SVPWM relies on the representation of the output voltage the inverter

output as space vector or space phasors. Space vector representation of the output

voltages of the inverter is realized of the implementation of SVPWM [2,8,16].

Space vector simultaneously represents three phases quantities as one rotating

vector, hence each of phase is not considered separately. The three phases are assumed

as only one quantity. In recent years, the space vector theory demonstrated some

improvement for both the output crest voltage and the harmonic copper loss [8,16]. The

maximum output voltage based on the space vector theory is √

⁄ = 1.55 times as large

as the conventional sinusoidal modulation [8,14,16]. It enables to feed the motor with a

higher voltage than the easier sub-oscillation modulation method. This modulator

allows to have a higher torque at high speeds, and a higher efficiency [6,8,16]. The

space vector is defined as

[

] (2.6)

Where , and are three phase quantities of voltages, current and fluxes. In the

inverter PWM, the voltage space vectors considered.

Since the inverter can attain either +5 or -5 or 0 , i.e only two states,

the total possible output are = 8( 000, 001, 010, 011, 100, 101, 110, 111). Here 0

indicates switch is ‘OFF’ and 1 indicates switch is ‘ON’. Thus there are six active

switching states an two zero switching states. The operation of the lower switch are

complimentary. By using equation 2.5 and Table 2.1 shows the possible space vector

are computed [8,16].

14

Table 2.1: Phase to neutral space vector for three phase voltage source inverter [8]

Switching states Space vector number Phase to neutral Voltage

Space Vector

000 7 0

001 5

010 3

011 4

100 1

101 6

110 2

111 8 0

The space vector is graphically in Figure 2.6 below. The hexagon consists of six

distinct sector spanning over 360 degrees with each sector of 60 degrees [8,16].

7,8

Sector I

Sector II

Sector III

Sector IV

Sector V

Sector VI

(100)

Real

Img

(110)(010)

(011)

(001) (101)

1

23

4

56

π/3

Reference

Trajoctory

Figure 2.6: Voltage space vector locations corresponding to different switching states.

15

Space vector 1, 2…6 called the active states and 7, 8 called zero states vectors. Are

redundant vector but they are used to minimize the switching frequency. The references

voltage follows a circular trajectory in a linear modulation range and the output is

sinusoidal. The reference trajectory will change over the modulation and the trajectory

will be hexagon boundary when the inverter is operating in the six-step mode [16].

In implementing the SVPWM, the references voltage is synthesized by using

the nearest two neighboring active vector and zero vectors. The choice of the active

vector upon the sector vector is located. Hence, it is important to locate the position of

the reference voltage. Then the references vector located will be used for SVPWM

implementation to be identified. After identifying the vector to be used next task is to

find time of application of each vector called the ‘dwell time’. The output voltage

frequency of the inverter is the same as the speed reference voltage and the output

voltage magnitude is the same as the magnitude of the reference voltage[16].

2.6 Permanent magnet synchronous motor

Among all of the existing motors on the market are three ‘classical’ motors: the Direct

Current with commutators (wound field) and two Alternative Current motors the

synchronous and the asynchronous motors. These motors, when properly controlled,

produce constant instantaneous torque (very little torque ripple) and operate from pure

DC or AC sinewave supplies [22]. Figure 2.7 shows the classification of electric

motors.

16

Electric Motors

AC Motor DC Motor

Asynchronous Synchronous

Induction Motor Brushless Sinewave Hysteresis Step Reluctance

Permanent

MagnetWound Field

Figure 2.7: Classification of electric motors [22].

A PMSM is a motor that uses permanent magnets to produce the air gap

magnetic field rather than using electromagnets. These motors have significant

advantages, attracting the interest of researchers and industry for use in many

applications such as spinning mills, robotics, electric vehicles, cement mills and etc [1-

6].

The synchronous motor (SM) has two primary parts. The non-moving is called

the stator and the moving, usually inside the stator, is called the rotor. SM can be built

in different structures [21]. To enable a motor to rotate two fluxes are needed, one from

the stator and the other one from the rotor. For this process several motor

configurations are possible. From the stator side three-phase motors are the most

common as illustrated in Figure 2.8. There are mainly two ways to generate a rotor

flux. One uses rotor windings fed from the stator and the other is made of permanent

magnets and generates a constant flux by itself [21,22].

17

Figure 2.8: A three-phase synchronous motor with a one permanent magnet pair pole

rotor

Motors have been constructed with two to fifty or more magnet poles. A greater

number of poles usually create a greater torque for the same level of current. This is

true up to a certain point where due to the space needed between magnets, the torque no

longer increases. Advanced magnet materials such as Samarium Cobalt (SmCo)

magnets and Neodymium Iron Boride (NdFeB) magnets permit a considerable

reduction in motor dimensions while maintaining a very high power density. In the case

of embedded systems where the space occupied is important, a PMSM is usually

preferred to an AC synchronous motor with brushes [21-24].

The SM with rotor windings maintains maximum efficiency by regulating the

rotor currents and then the flux. For high-speed systems where high efficiency is

required, AC synchronous motors with rotor windings may be a good compromise.

Figure 2.9: Surface permanent magnet motor [21]

18

2.6.1 Advantages of PMSM

The application of PMSM technology and its advantages over the conventionally used

induction principle. The main points which can be considered while summarizing this

advantage are as [24]:

(i). PMSM provides higher power density for their size compared to induction

machine. This is because with an induction machine, part of the stator current is

required to "induce" rotor current in order to produce rotor flux. These

additional currents generate heat within the motor where as, the rotor flux is

already established in a PMSM by the permanent magnets on the rotor.

(ii). With the low power density it aids compactness. This results in development of

a PMSM with low rotor inertia, which is capable of providing faster response.

(iii). It is operating at a higher power factor compared to induction motor (IM) due to

the absence of magnetizing current.

(iv). The design of controller required for the design of speed control of the fan

operated by PMSM is simple. The PMSM also provides a key feature of

operating at high efficiency with low speeds, thus giving all round efficient

operation for the cooling tower at high and low speeds.

19

2.7 Fuzzy logic controller

Fuzzy Logic Controller (FLC) is a technique to embody human-like thinking into a

control system. FLC can be designed to emulate human deductive thinking, that is, the

process people use to infer conclusions from what they know. FLC has been primarily

applied to the control of processes through fuzzy linguistic descriptions [1-4,12,17-20].

The FLC initially converts the crisp error and change in error variables into

fuzzy variables and then are mapped into linguistic labels [17,18-20]. FLC is utilized to

design controllers for plants with complex dynamics and high nonlinearity model. In a

motor control system, the function of FLC is to convert linguistic control rules into

control strategy based on heuristic information or expert knowledge[1,2,17-20]].

It has been reported that fuzzy controllers are more robust to plant parameter

changes than classical PI or PID controllers and have better noise rejection capabilities.

The proposed scheme exploits the simplicity of the Mamdani type fuzzy systems that

are used in the design of the controller [1,2,4,12,19&20]. The Figure 2.11 illustrated the

block diagram of FLC structure.

FuzzificationKnowledge Rule

BasedDefuzzification Output

Error

Change

Error

Figure 2.10: The basic structure of fuzzy logic controller [17]

The structure of FLC is shown in Figure 2.11. There are four main parts for

fuzzy logic approach. The first part is ‘fuzzification unit’ to convert the input variable

to the linguistic variable or fuzzy variable [17]. The second part is ‘knowledge base’ to

keep the necessary data for setting the control method by the expert engineer. The

‘decision making logic’ or the inference engine is the third part to imitate the human

decision using rule bases and data bases from the second part. The final part is

20

‘defuzzification unit’ to convert the fuzzy variable to easy understanding variable

[1,2,19,20].

2.8 Previous works

From the review has been made since 1995 until 2011 for PMSM Drive System, there

were several of controller, method or technique has been proposed in order to optimize

the efficiency. PMSM have been widely used in motion control applications [1–9&12]

but among these, the IPMSM have been of a particular attention due to their distinct

features of low-torque ripples and high power density [1011 13&14].

Table 2.2: Survey on previous works

References 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

PMSM ∕ ∕ ∕ ∕ ∕ ∕ ∕ ∕

∕ ∕

∕ ∕

controller ∕ ∕ ∕ ∕ ∕

∕

∕

∕ ∕ ∕ ∕ ∕ ∕ ∕

From the Table 2.2 above, most of the researchers focus on the controller in

order to improve the efficiency. The numbering in the Figure represent of references

number. But some of them used Interior Permanent Magnet Synchronous Motor

(IPMSM) as their electric rotating load. This is because with permanent magnets buried

inside the rotor, features such as smooth rotor surface and reduced air-gap will result in

a robust mechanical construction and thus permitting higher speed with quiet operation

and better dynamic performance [14]. It’s different with [2], which is used no position

sensor to controlled the magnitude of the voltages in order to maintain a constant stator

flux linkage in the PMSM.

For paper [5,7&12], all are deals with analysis and hardware implementation,

and methodologies in VC and described of FOC technique. FOC or VC is mostly used

21

as it provides superior torque to inertia ratio, high controllability and greater power

density as in [1,5,7-9,12&16]. This topics will discussed about recent previous works

and the comparison regarding to the PMSM Drive speed control based on FLC.

In 2011, B.Adhavan et al was performed the simulation of speed control system on

fuzzy logic approach for an indirect vector controlled permanent magnet synchronous drive by

applying space vector modulation. The method of formulation of control algorithms allows

implementing heuristic strategies. From this research found that the initial starting torque of the

machine is reduced so the initial stator current drawn by the motor is also reduced [19].

Chalermpon Pewmaikam et al. (2012) performing their research on a torque control

system with an adaptive fuzzy logic compensator for torque control and the torque estimator of

the machine for torque measurement. This method can improve the efficiency of the torque

control system. Additionally, this method leads to the process that can apply to decrease the

calibration time of the automatic screw machines.

In year 2011 also Siti Noormiza Mat Isa et al developed the control strategy focuses on

fuzzy rule base which are contribute to some level of output in obtaining the desired

performance. Two FLCs with reduced rule base (9- rules and 7-rules) are designed and the

performance results are compared and evaluated with the standard FLC (49-rules). The

simplification of rule base is determined by eliminating some of rule bases that are infrequently

fired by the PMSM drive. The simplified FLCs produce almost equivalent performance to

‘Standard FLC’ in some cases and better performance than ‘Standard FLC’ in some other cases.

Therefore, it feasible to reduce the rule base from 49-rules to 9-rules or 7-rules in

implementation of vector controlled PMSM drives.The test results on the performance of the

DSP based fuzzy pre compensated PI speed controller for vector controlled PMSM drive have

confirmed the validity of the algorithm developed to analyse the behaviour of the PMSM drive

system. The assembly language programming for the implementation on DSP has resulted in

the use of reduced hardware [2].

Amit Vilas Sant and K. R. Rajagopal in 2009 founded that The former method based

on switching often causes chattering effects, and later method demands larger execution time

because of inclusion of separate switching algorithms. This paper reports the vector control of

PMSM with hybrid fuzzy-PI speed controller with switching functions calculated based on the

weights for both the controller outputs using the output of (a) only the fuzzy controller, (b) only

the PI controller and (c) a combination of the outputs of both the controllers. These switching

functions are very simple and effective and do not demand any extra computations to arrive at

the hybrid fuzzy-PI controller outputs. The hybrid fuzzy-PI speed controllers with the three

switching functions calculated based on the weights for both the controller outputs using the

output of only the fuzzy controller, only the PI controller and the combination of the outputs of

22

both the controllers, are performing better than the PI alone and fuzzy alone speed controllers

[1].

In 2003, Bhim Singh with his friends was discovered that the deals with the analysis

and hardware implementation of a Fuzzy Pre compensated Proportional-Integral (FPPI) speed

controller for Vector Controlled (VC) Permanent Magnet Synchronous Motor (PMSM) drive

using a digital signal processor. The power circuit of the PMSM drive consists of insulated gate

bipolar transistor (IGBT) based Voltage Source Inverter (VSI) and the gate driver circuit. The

hardware of control circuit has current sensors and interfacing circuits. The simulation model of

the drive system is developed in MATLAB environment with Simulink, PSB and FLC

toolboxes to analyze the performance of PMSM drive system. Simulated results are validated

with test results of the PMSM drive for starting, speed reversal and load perturbation. The test

results on the performance of the DSP based fuzzy pre compensated PI speed controller for

vector controlled PMSM drive have confirmed the validity of the algorithm developed to

analyse the behaviour of the PMSM drive system. The assembly language programming for the

implementation on DSP has resulted in the use of reduced hardware [3].

CHAPTER 3

METHODOLOGY

3.1 Overview

This chapter described the method that used for this project. In order to complete this

project, the development a method and step to make sure this project successful

without any problems and to avoid confusing and unprepared. Lots of information is

required in relation to full fill this project. This project development is divided into

two main phases.

The phase A consisting extensive literature reviews were done on related

knowledge to assist in any ways that it may. Such reviews are based on international

publications, websites, and engineering books represented the development of

PMSM system based on MATLAB Simulink and establish the field oriented control

simulation.

The second part which at phase B reflected to development of intelligent

control system that used Fuzzy Logic Controller and SVPWM module. Lastly come

out with data and result analysis or outcome of this project. The development of this

project can be summarized in term of flow chart diagram such as shown in

APPENDIX A.

24

3.2 System Architecture

Figure 3.1 shows the block diagram proposed system. In tradional PI controller it

suffers from overshoots of response, when some unknown nonlinear are present in

the system [6,17,19&20]. The fuzzy logic controller overcomes this disadvantage

[1,2,12&19]. The fuzzy logic executes the rule base taking the input and gives the

output by defuzzification, input are speed error and change in speed error the output

will be the torque limit which equivalent with Iqs.

Figure 3.1: Block diagram of proposed system [6].

The outputs of the current controller are passed through the inverse Park

transform and a new stator voltage vector is impressed to the motor using the space

vector pulse width modulation (SVPWM) technique [7,14]. In order to control the

mechanical speed of the motor, In order to control the mechanical speed of the

motor, an outer loop is driving the reference current isq [1,2&3]. The PI regulator

compares the speed set point with the measured mechanical speed of the rotor and

produces the stator current quadrature axis reference, isq. That is the speed controller

outputs a reference torque, which is proportional to the quadrature-axis stator current

component isq. The mechanical speed reference is denoted ωref [1,2&3].

59

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61

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